This invention relates generally to aircraft engine power management schemes and more particularly, to removing at least one hyperplane from a control space of an engine management scheme.
An aircraft engine power management schedule specifies an engine power setting, which varies by flight condition and operational mode. The power management schedule is an important path deliverable in an aircraft certification process, which is developed from a quoted thrust rating, an average engine characteristics model, an engine control architecture, and an airplane flight range.
Desired power settings are calculated from an average engine in-flight thrust model using target thrust levels obtained from a quoted thermodynamic cycle model. Unfortunately, these calculations are typically too complicated for real-time engine control, so an interpolating controller (Full Authority Digital Engine Controllors “FADEC”) is being used. The power management problem then becomes a problem in selecting the best subset of control space points to use in the controller. Current FADEC controllers use vectors of values in each dimension to specify points. For example, using the following values:
Altitude, Feet ={0, 1000, 10000, 25000, 30000, 40000}Temperature, Degrees C. ={−80, −40, −20, 0, 20, 40}AirSpeed, MachNumber ={0.1, 0.3, 0.5, 0.7, 0.9}PowerLevel ={takeoff, maxClimb}
provides for 3600 (6×6×5×2=3600) points on the control surface. A typical situation for a single power level often has over 5000 points on the control surface. Each power level is treated separately, resulting in a three-dimensional control space.
Optimization is achieved by reducing this target matrix which reduces the memory and throughput requirements of an engine controller. However, the table reduction is subject to constraints limiting overboost and underboost, while providing adequate operational margins on rotor speeds, exhaust gas temperature, etc.
Currently, this optimization is conducted manually using a visualization tool to find near-linear sectors across planes in the control space, deleting planes to reduce table size, and adjusting the levels of the remaining points to ensure that both the adjusted and interpolated values still achieve the overall requirements. However, there are drawbacks to the current manual optimization. One specific drawback is that it currently requires a substantial amount of labor to perform the manual optimization.